Resolving geographic units that do not neatly coincide is a common problem in spatial data analysis. The method outline here attempts to conflate King County Health Reporting Areas (HRAs) to US Census tracts. In the cases where a given tract is entirely within an HRA, that tract receives the HRA’s unique identifier (HRA_ID). On the other hand, in cases where a given tract overlaps multiple HRAs, block-level census data is used to determine which HRA ID to assign to the tract.
This method provides three alternatives of block-level counts that can be used:
| Count Type | Variable ID | Source |
|---|---|---|
| Population | POP |
Table P1, U.S. Census Bureau, 2010 Census |
| Housing Units | HU |
Table H1, U.S. Census Bureau, 2010 Census |
| Population in Housing Units | HUPOP |
Table H10, U.S. Census Bureau, 2010 Census |
The following actions are performed in this method:
class = SpatialPointsDataFrame)sp::over())POP,HU,POPHU) are summedAfter running the assignment algorithm, it is clear that the POP and POPHU variables result in the same HRA assignments. HU differs from the other two variables in three of the tracts:
| GEOID_TR | HRA_POP | HRA_POPHU | HRA_HU |
|---|---|---|---|
| 53033022202 | Kirkland North | Kirkland North | Kirkland |
| 53033025001 | Bellevue-South | Bellevue-South | Newcastle/Four Creeks |
| 53033028801 | SeaTac/Tukwila | SeaTac/Tukwila | Des Moines/Normandy Park |